Abstract
So-called ‘Evolutionary potentials’ for protein structure prediction are derived using a single experimental protein structure and all three-dimensional models of its homologous sequences.
Highlights
Comparative protein structure prediction is typically implemented in four main steps: fold assignment, target-template alignment, model building, and model assessment [1]
Two major variables impact the derivation of EVOLUTIONARY POTENTIAL (EvP): the stringency of the clustering process and the deepness of the multiple sequence alignments (MSAs)
EvPs calculated from the strictest clustering corresponding to 90% sequence and structural identity resulted in the most accurate assessment of the model accuracy as measured by their maximal accuracy (ACC), the area under the curve (AUC), false positive rate (FPR), and true positive rate (TPR)
Summary
Comparative protein structure prediction is typically implemented in four main steps: fold assignment, target-template alignment, model building, and model assessment [1]. The starting point in comparative modeling identifies protein structures related to the target sequence. This initial step is normally performed using profile-based search methods such as PSI-BLAST, hidden Markov models or profile-profile methods [2]. Once a fold has been assigned, a specialized alignment method is used to optimally align the target sequence with the template structure. The target-template alignment is used to build a structure model of the target sequence. The model assessment step predicts whether or not the correct template was assigned and at least an approximately correct alignment was produced. In this work we describe the development and implementation of a new method for model assessment
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